ML Engineer

ML Engineer

Hybrid Arlington VA or remote (Boston, Bay Area, San Diego, Los Angeles)

Note: This role has been reconstructed using Quartermaster's company context, team requirements and defense-tech environment because the original document contained limited ML-specific details.

Role Overview

Quartermaster is seeking a highly skilled ML Engineer to design, build and deploy machine learning systems that support maritime intelligence and edge AI applications. The role focuses on taking models from research to production while ensuring scalability, reliability and operational performance in real-world environments.

Key Responsibilities

• Design and build scalable machine learning pipelines from data ingestion to deployment

• Develop, train and optimize ML models for sensor-based and maritime intelligence applications

• Work with high-dimensional sensor, geospatial and time-series datasets

• Develop and maintain data labeling and dataset versioning workflows

• Build systems for model monitoring, retraining and drift detection

• Partner with Data Scientists and Systems Engineers to deploy production-ready solutions

• Support edge-deployed AI systems and optimize model performance in constrained environments

• Design tools for experiment tracking and model performance evaluation

• Participate in system integration and testing activities

• Ensure data quality, validation and production reliability

Technical Skills

• Strong Python programming skills

• Experience with machine learning frameworks such as TensorFlow or PyTorch

• Experience with pandas, NumPy and scikit-learn

• Knowledge of SQL and data engineering concepts

• Understanding of ML Ops concepts

• Familiarity with Docker, cloud platforms and CI/CD workflows

• Experience working with APIs and distributed systems

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence or related field

• 5–10 years of relevant machine learning experience

• Strong understanding of machine learning fundamentals

• Experience deploying models into production

• Experience with real-world ML systems and performance optimization

Preferred Qualifications

• Experience with maritime systems, autonomous systems, aerospace or defense technology

• Experience with sensor fusion and perception systems

• Government or regulated industry exposure

• Startup experience in fast-moving environments

• Security clearance eligibility is a plus

Ideal Candidate Profile

• Strong problem-solving mindset

• Ability to work independently

• Comfortable with ambiguity and fast iteration cycles

• Can ship quickly and adapt to changing requirements

• Startup mentality with strong ownership

Compensation

$230K and Competitive Equity

Location

Hybrid Arlington VA or remote (Boston, Bay Area, San Diego, Los Angeles)